Arguably, nothing messes with a firm’s loyalty and/or CRM strategy more than a multitude of false consumer profiles polluting a CRM database. In seeking to elevate one’s marketing engagement index, it’s often helpful to understand the demographic profile of a consumer. But if such a consumer does not self-report this, or if such data is not inferred, then firms are at the mercy of the garbage.
Interestingly, a research team claims in their research paper
The profiles users may contain fake information. We believe that our proposed algorithm can be used to identify and refine the profiles which contain bogus demographic information.
Essentially, this team analyzed web log files for search patterns and used an algorithm to predict gender or age. They claim a lift in accuracy of 30.4% on gender prediction and 50.3% on age prediction over traditional methodologies.
What makes this exciting is that, assuming futher testing bears out the team’s claims, companies like HitWise or WebTrends can incorporate this algorithm into its search pattern analsysis products. Firms can then use this core demographic information to craft more relevant landing pages, calls to actions, etc, on their websites.